Critical Analysis of Distributed Localization Algorithms for Wireless Sensor Networks

Singh, Santar Pal; Sharma, Shelly

doi:10.5815/ijwmt.2016.04.07

Cited by 14 publications

(7 citation statements)

References 29 publications

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“…Various metaheuristic techniques have been implemented for enhancing the localization technique to raise the accuracy of actual localization method. Singh et al [10] employed an enhanced method for localization and later, utilized PSO method to determine the outcomes. Zhao et al [11] presented a localization technique depending upon hybrid chaotic approach.…”

Section: Literature Reviewmentioning

confidence: 99%

A Modified Search and Rescue Optimization Based Node Localization Technique in WSN

Jacob¹,

Muthumayil²,

Kavitha³

et al. 2022

Computers, Materials &Amp; Continua

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Wireless sensor network (WSN) is an emerging technology which find useful in several application areas such as healthcare, environmental monitoring, border surveillance, etc. Several issues that exist in the designing of WSN are node localization, coverage, energy efficiency, security, and so on. In spite of the issues, node localization is considered an important issue, which intends to calculate the coordinate points of unknown nodes with the assistance of anchors. The efficiency of the WSN can be considerably influenced by the node localization accuracy. Therefore, this paper presents a modified search and rescue optimization based node localization technique (MSRO-NLT) for WSN. The major aim of the MSRO-NLT technique is to determine the positioning of the unknown nodes in the WSN. Since the traditional search and rescue optimization (SRO) algorithm suffers from the local optima problem with an increase in number of iterations, MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the technique. The application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO algorithm. In order to validate the effective node localization performance of the MSRO-NLT algorithm, a set of simulations were performed to highlight the supremacy of the presented model. A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.

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Section: Literature Reviewmentioning

confidence: 99%

A Modified Search and Rescue Optimization Based Node Localization Technique in WSN

Jacob¹,

Muthumayil²,

Kavitha³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Three anchor nodes as the center to construct three squares are applied, in which the shadow area of the intersection of three squares is the overall workable area of the unknown nodes, and the initial population is generated randomly in the functional area. Singh et al applied an improved algorithm for localization and then used particle swarm optimization to refine the results [36]. Zhao et al proposed an improved localization algorithm based on hybrid chaotic strategy [10].…”

Section: Related Workmentioning

confidence: 99%

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Han

et al. 2020

Sensors

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The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements.

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“…Research Article [1] authors have reported the different varieties of localization algorithms based on various estimations. The comparative analysis was made and concluded each schemes with features.…”

Section: Eai Endorsed Transactions On Energy Web and Information Techmentioning

confidence: 99%

Exploration on Increasing Packet delivery rate in WSN using Cluster Approach

Mahaveerakannan¹,

Dhas²,

Ganesan³

2018

EAI Endorsed Transactions on Energy Web

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Wireless Sensor Network (WSN) plays a vital role and part of real time communication applications. Location of unknown node is difficult to find in the presence of mobile sensor nodes. Navigator plays an important role in identifying network fault and unknown node location. In existing schemes, either trilateration or geographical position routing were deployed to increase the location accuracy. In this research, Neighbour based Cluster Location Aware Routing (NCLAR) is proposed to achieve more packet delivery rate with high location accuracy. It consists of three phases. In first phase, cluster region is formed with less signal delay value and more signal strength. In second phase, neighbour node routing table is constructed and updated with addition of more fields. These fields are reliability, probability of successful transmission of packets and delay. The back off timer is estimated to update the table within a periodical time. In last phase, location status navigator is calculated to increase location accuracy and to maximize the packet delivery ratio. Based on the simulation results, the proposed scheme NCLAR achieves high location accuracy, more packet delivery ratio, less overhead, less delay and high network lifetime.

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Critical Analysis of Distributed Localization Algorithms for Wireless Sensor Networks

Cited by 14 publications

References 29 publications

A Modified Search and Rescue Optimization Based Node Localization Technique in WSN

A Modified Search and Rescue Optimization Based Node Localization Technique in WSN

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

Exploration on Increasing Packet delivery rate in WSN using Cluster Approach

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